Bakcbone. We evaluate our quantization method on two popular vision transformer implementation: DeiT [1]} and Swin Transformer [2]}. The DeiT-S, DeiT-B, Swin-T and Swin-S are adopted as the backbone models, whose Top-1 accuracy on ImageNet dataset are 79.9%, 81.8%, 81.2%, and 83.2% respectively. For a fair comparison, we utilize the official implementation of DeiT and Swin Transformer.
